| // Copyright 2011 Google Inc. All Rights Reserved. |
| // |
| // This code is licensed under the same terms as WebM: |
| // Software License Agreement: http://www.webmproject.org/license/software/ |
| // Additional IP Rights Grant: http://www.webmproject.org/license/additional/ |
| // ----------------------------------------------------------------------------- |
| // |
| // Spatial prediction using various filters |
| // |
| // Author: Urvang (urvang@google.com) |
| |
| #include "./filters.h" |
| #include <assert.h> |
| #include <stdlib.h> |
| #include <string.h> |
| |
| #if defined(__cplusplus) || defined(c_plusplus) |
| extern "C" { |
| #endif |
| |
| //------------------------------------------------------------------------------ |
| // Helpful macro. |
| |
| # define SANITY_CHECK(in, out) \ |
| assert(in != NULL); \ |
| assert(out != NULL); \ |
| assert(width > 0); \ |
| assert(height > 0); \ |
| assert(bpp > 0); \ |
| assert(stride >= width * bpp); |
| |
| static WEBP_INLINE void PredictLine(const uint8_t* src, const uint8_t* pred, |
| uint8_t* dst, int length, int inverse) { |
| int i; |
| if (inverse) { |
| for (i = 0; i < length; ++i) dst[i] = src[i] + pred[i]; |
| } else { |
| for (i = 0; i < length; ++i) dst[i] = src[i] - pred[i]; |
| } |
| } |
| |
| //------------------------------------------------------------------------------ |
| // Horizontal filter. |
| |
| static WEBP_INLINE void DoHorizontalFilter(const uint8_t* in, |
| int width, int height, int bpp, int stride, int inverse, uint8_t* out) { |
| int h; |
| const uint8_t* preds = (inverse ? out : in); |
| SANITY_CHECK(in, out); |
| |
| // Filter line-by-line. |
| for (h = 0; h < height; ++h) { |
| // Leftmost pixel is predicted from above (except for topmost scanline). |
| if (h == 0) { |
| memcpy((void*)out, (const void*)in, bpp); |
| } else { |
| PredictLine(in, preds - stride, out, bpp, inverse); |
| } |
| PredictLine(in + bpp, preds, out + bpp, bpp * (width - 1), inverse); |
| preds += stride; |
| in += stride; |
| out += stride; |
| } |
| } |
| |
| static void HorizontalFilter(const uint8_t* data, int width, int height, |
| int bpp, int stride, uint8_t* filtered_data) { |
| DoHorizontalFilter(data, width, height, bpp, stride, 0, filtered_data); |
| } |
| |
| static void HorizontalUnfilter(const uint8_t* data, int width, int height, |
| int bpp, int stride, uint8_t* recon_data) { |
| DoHorizontalFilter(data, width, height, bpp, stride, 1, recon_data); |
| } |
| |
| //------------------------------------------------------------------------------ |
| // Vertical filter. |
| |
| static WEBP_INLINE void DoVerticalFilter(const uint8_t* in, |
| int width, int height, int bpp, int stride, int inverse, uint8_t* out) { |
| int h; |
| const uint8_t* preds = (inverse ? out : in); |
| SANITY_CHECK(in, out); |
| |
| // Very first top-left pixel is copied. |
| memcpy((void*)out, (const void*)in, bpp); |
| // Rest of top scan-line is left-predicted. |
| PredictLine(in + bpp, preds, out + bpp, bpp * (width - 1), inverse); |
| |
| // Filter line-by-line. |
| for (h = 1; h < height; ++h) { |
| in += stride; |
| out += stride; |
| PredictLine(in, preds, out, bpp * width, inverse); |
| preds += stride; |
| } |
| } |
| |
| static void VerticalFilter(const uint8_t* data, int width, int height, |
| int bpp, int stride, uint8_t* filtered_data) { |
| DoVerticalFilter(data, width, height, bpp, stride, 0, filtered_data); |
| } |
| |
| static void VerticalUnfilter(const uint8_t* data, int width, int height, |
| int bpp, int stride, uint8_t* recon_data) { |
| DoVerticalFilter(data, width, height, bpp, stride, 1, recon_data); |
| } |
| |
| //------------------------------------------------------------------------------ |
| // Gradient filter. |
| |
| static WEBP_INLINE int GradientPredictor(uint8_t a, uint8_t b, uint8_t c) { |
| const int g = a + b - c; |
| return (g < 0) ? 0 : (g > 255) ? 255 : g; |
| } |
| |
| static WEBP_INLINE |
| void DoGradientFilter(const uint8_t* in, int width, int height, |
| int bpp, int stride, int inverse, uint8_t* out) { |
| const uint8_t* preds = (inverse ? out : in); |
| int h; |
| SANITY_CHECK(in, out); |
| |
| // left prediction for top scan-line |
| memcpy((void*)out, (const void*)in, bpp); |
| PredictLine(in + bpp, preds, out + bpp, bpp * (width - 1), inverse); |
| |
| // Filter line-by-line. |
| for (h = 1; h < height; ++h) { |
| int w; |
| preds += stride; |
| in += stride; |
| out += stride; |
| // leftmost pixel: predict from above. |
| PredictLine(in, preds - stride, out, bpp, inverse); |
| for (w = bpp; w < width * bpp; ++w) { |
| const int pred = GradientPredictor(preds[w - bpp], |
| preds[w - stride], |
| preds[w - stride - bpp]); |
| out[w] = in[w] + (inverse ? pred : -pred); |
| } |
| } |
| } |
| |
| static void GradientFilter(const uint8_t* data, int width, int height, |
| int bpp, int stride, uint8_t* filtered_data) { |
| DoGradientFilter(data, width, height, bpp, stride, 0, filtered_data); |
| } |
| |
| static void GradientUnfilter(const uint8_t* data, int width, int height, |
| int bpp, int stride, uint8_t* recon_data) { |
| DoGradientFilter(data, width, height, bpp, stride, 1, recon_data); |
| } |
| |
| #undef SANITY_CHECK |
| |
| // ----------------------------------------------------------------------------- |
| // Quick estimate of a potentially interesting filter mode to try, in addition |
| // to the default NONE. |
| |
| #define SMAX 16 |
| #define SDIFF(a, b) (abs((a) - (b)) >> 4) // Scoring diff, in [0..SMAX) |
| |
| WEBP_FILTER_TYPE EstimateBestFilter(const uint8_t* data, |
| int width, int height, int stride) { |
| int i, j; |
| int bins[WEBP_FILTER_LAST][SMAX]; |
| memset(bins, 0, sizeof(bins)); |
| // We only sample every other pixels. That's enough. |
| for (j = 2; j < height - 1; j += 2) { |
| const uint8_t* const p = data + j * stride; |
| int mean = p[0]; |
| for (i = 2; i < width - 1; i += 2) { |
| const int diff0 = SDIFF(p[i], mean); |
| const int diff1 = SDIFF(p[i], p[i - 1]); |
| const int diff2 = SDIFF(p[i], p[i - width]); |
| const int grad_pred = |
| GradientPredictor(p[i - 1], p[i - width], p[i - width - 1]); |
| const int diff3 = SDIFF(p[i], grad_pred); |
| bins[WEBP_FILTER_NONE][diff0] = 1; |
| bins[WEBP_FILTER_HORIZONTAL][diff1] = 1; |
| bins[WEBP_FILTER_VERTICAL][diff2] = 1; |
| bins[WEBP_FILTER_GRADIENT][diff3] = 1; |
| mean = (3 * mean + p[i] + 2) >> 2; |
| } |
| } |
| { |
| WEBP_FILTER_TYPE filter, best_filter = WEBP_FILTER_NONE; |
| int best_score = 0x7fffffff; |
| for (filter = WEBP_FILTER_NONE; filter < WEBP_FILTER_LAST; ++filter) { |
| int score = 0; |
| for (i = 0; i < SMAX; ++i) { |
| if (bins[filter][i] > 0) { |
| score += i; |
| } |
| } |
| if (score < best_score) { |
| best_score = score; |
| best_filter = filter; |
| } |
| } |
| return best_filter; |
| } |
| } |
| |
| #undef SMAX |
| #undef SDIFF |
| |
| //------------------------------------------------------------------------------ |
| |
| const WebPFilterFunc WebPFilters[WEBP_FILTER_LAST] = { |
| NULL, // WEBP_FILTER_NONE |
| HorizontalFilter, // WEBP_FILTER_HORIZONTAL |
| VerticalFilter, // WEBP_FILTER_VERTICAL |
| GradientFilter // WEBP_FILTER_GRADIENT |
| }; |
| |
| const WebPFilterFunc WebPUnfilters[WEBP_FILTER_LAST] = { |
| NULL, // WEBP_FILTER_NONE |
| HorizontalUnfilter, // WEBP_FILTER_HORIZONTAL |
| VerticalUnfilter, // WEBP_FILTER_VERTICAL |
| GradientUnfilter // WEBP_FILTER_GRADIENT |
| }; |
| |
| //------------------------------------------------------------------------------ |
| |
| #if defined(__cplusplus) || defined(c_plusplus) |
| } // extern "C" |
| #endif |